Remake with symbolic map (#1835)

src/ModelingToolkit.jl

@@ -5,7 +5,7 @@ module ModelingToolkit
 using DocStringExtensions
 using AbstractTrees
 using DiffEqBase, SciMLBase, ForwardDiff, Reexport
-using SciMLBase: StandardODEProblem, StandardNonlinearProblem
+using SciMLBase: StandardODEProblem, StandardNonlinearProblem, handle_varmap
 using Distributed
 using StaticArrays, LinearAlgebra, SparseArrays, LabelledArrays
 using InteractiveUtils

src/variables.jl

@@ -46,7 +46,8 @@ applicable.
 function varmap_to_vars(varmap, varlist; defaults = Dict(), check = true,
                         toterm = Symbolics.diff2term, promotetoconcrete = nothing,
                         tofloat = true, use_union = false)
-    varlist = map(unwrap, varlist)
+    varlist = collect(map(unwrap, varlist))
+
     # Edge cases where one of the arguments is effectively empty.
     is_incomplete_initialization = varmap isa DiffEqBase.NullParameters ||
                                    varmap === nothing
@@ -97,7 +98,7 @@ function _varmap_to_vars(varmap::Dict, varlist; defaults = Dict(), check = false
         varmap[p] = fixpoint_sub(v, varmap)
     end
 
-    missingvars = setdiff(varlist, keys(varmap))
+    missingvars = setdiff(varlist, collect(keys(varmap)))
     check && (isempty(missingvars) || throw_missingvars(missingvars))
 
     out = [varmap[var] for var in varlist]
@@ -107,6 +108,17 @@ end
     throw(ArgumentError("$vars are missing from the variable map."))
 end
 
+"""
+$(SIGNATURES)
+
+Intercept the call to `handle_varmap` and convert it to an ordered list if the user has
+  ModelingToolkit loaded, and the problem has a symbolic origin.
+"""
+function SciMLBase.handle_varmap(varmap, sys::AbstractSystem; field = :states, kwargs...)
+    out = varmap_to_vars(varmap, getfield(sys, field); kwargs...)
+    return out
+end
+
 struct IsHistory end
 ishistory(x) = ishistory(unwrap(x))
 ishistory(x::Symbolic) = getmetadata(x, IsHistory, false)

test/odesystem.jl

@@ -224,6 +224,23 @@ for p in [prob1, prob14]
     @test Set(Num.(parameters(sys)) .=> p.p) == Set([k₁ => 0.04, k₂ => 3e7, k₃ => 1e4])
     @test Set(Num.(states(sys)) .=> p.u0) == Set([y₁ => 1, y₂ => 0, y₃ => 0])
 end
+# test remake with symbols
+p3 = [k₁ => 0.05,
+    k₂ => 2e7,
+    k₃ => 1.1e4]
+u01 = [y₁ => 1, y₂ => 1, y₃ => 1]
+prob_pmap = remake(prob14; p = p3, u0 = u01)
+prob_dpmap = remake(prob14; p = Dict(p3), u0 = Dict(u01))
+for p in [prob_pmap, prob_dpmap]
+    @test Set(Num.(parameters(sys)) .=> p.p) == Set([k₁ => 0.05, k₂ => 2e7, k₃ => 1.1e4])
+    @test Set(Num.(states(sys)) .=> p.u0) == Set([y₁ => 1, y₂ => 1, y₃ => 1])
+end
+sol_pmap = solve(prob_pmap, Rodas5())
+sol_dpmap = solve(prob_dpmap, Rodas5())
+
+@test sol_pmap.u ≈ sol_dpmap.u
+
+# test kwargs
 prob2 = ODEProblem(sys, u0, tspan, p, jac = true)
 prob3 = ODEProblem(sys, u0, tspan, p, jac = true, sparse = true)
 @test prob3.f.jac_prototype isa SparseMatrixCSC